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Decision support and business intelligence systems

Decision Support Business Intelligence al Affiliation The Meaning of various terms: Operational BI, Analytics and OLAP Operational Business IntelligenceOperational Business Intelligence also known as real-time business Intelligence is the method to data analysis that involves management and optimization of daily business processes (White, 2005). The process delivers the right information at the right time to the correct business users so as to enable them to respond quickly to solve business problems and satisfy novel business needs. As a result, Operational BI assists organizations to function smarter and become more responsive and agile, and in turn it makes them to be competitive and enhance client satisfaction. Call center operators and most front office workers typically are the main targets of operational business intelligence. AnalyticsThis refers to the finding and communicating of important patterns in data, particularly in significant areas full of recorded info, and relies on synchronized application of operations research, statistics and computer software to ascertain performance. Business analytics makes sense of BI and relating them to trends and statistical algorithms to predict business outcomes. Brown (2007) offers a simpler explanation by asserting that they are gauges on the organizational platform that inform leaders and managers how the organizations are performing. Online Analytical Processing This is a piece of technology used in the organization of big business databases and offer sustenance to business intelligence, and the databases are split in cubes, and each is organized and planned to fit the way one retrieves and analyze data. What is KPI (Key Performance Indicators), and the distinguishing characteristics Key Performance Indicators are measurable business values estimated beforehand, that show the critical success factors of an organization (Parmenter, 2012). These assist organizations to predict, define and quantify progress towards the achievement of an organizational objectives and targets. People often misconstrue KPI and metric and use them interchangeably, in fact, KPI is a metric, but the converse cannot be true. KPI has ten distinguishing characteristics, and include: KPI reflect Strategic Value Drivers-and they are actions when executed perfectly can lead to success in the future. Second, KPIs are defined by the Executives, and the latter characterize value drivers in estimating sessions which predict both the short term and the long term tactical course of a company. Third, KPIs spill throughout a company and each and every group and at any level in a company is managed by ‘ an executive’, and the title is represented by divisional heads, managers, directors and supervisors amongst others. Others include being based on corporate standards, based on valid data, easy comprehension, KPIs are always relevant, provide context, empower users and they lead to positive action. Drawbacks of wholly relying on Financial Metrics for Performance Measurement Financial metrics performance measures profitability amongst other key financial measures, but they are limited compared to other performance measurements most often associated with the Kaplan and Norton’s Balanced Scorecard comprehensive measurement. The drawbacks of wholly relying on financial metrics for performance measurement include: First, financial metrics lack a close link to long term organizational strategies and instead focus merely on annual and short term projections. They do not handle progress in relation to customer requirements, competitors, and other non financial objectives which will ultimately guarantee profitability. Financial metrics are often referred to as traditional measures in the wake of new performance measures, and most experts argue that the drivers of success in organizations are intangible assets such as intellectual capital and customer loyalty more than quantified assets on the balance sheets. Financial metrics cannot measure intangible assets, rather other nonfinancial measures provides the accurate picture of these. Third, financial metrics are poor estimators of future financial performance, and that may arise from long-term decision made in the present periods. For instance, investments in R&D, or even customer satisfaction programs made currently. Fourth, financial measures are more susceptible to external changes in the performance measure that are beyond the manager or even company control and can range from changes in the economy to political situations. Legal, Privacy and Ethical issues related to Business Intelligence Legal, privacy and ethical issues in business intelligence are the principles, rules and contractual conducts that govern an individual and an organization specifically and generally respectively. Privacy is the claim by individuals against the access of data, and often the threat posed by the internet challenges the protection of privacy as data flow can be easily captured, monitored and stored during the movement in a network. In BI management, BI professionals similar to other professions face risks of making unethical practices in their decisions with respect to consumer, business and employees data. These three concepts; legal, privacy and ethics are touchy and controversies surround how organizations handle business decisions. In general legal issues govern data and the applications differ from jurisprudence to another as a law applied in one country on business intelligence is different from another applied in another country. An ethical issue that might confront a manager would the use of cheap data mining options to save money while at the same time putting the quality at a test. Further, the rapid growth in the use of mobile platforms as enterprise devices have thrown privacy, legal and ethical issues into question. The rapid improvement in the delivery of charts, graphs and other data visualization that have become legible on mobile platforms that manifests in smart phones and tablets, from the BI software vendors are facing these critical issues. References Brown, M. G. (2007). Beyond the balanced scorecard: Improving business intelligence with analytics. New York: Productivity Press. White, C. (January 01, 2005). The Next Generation of Business Intelligence: Operational BI. Dm Review, 15, 5, 34-37. Parmenter, D. (2012). Key performance indicators for government and non profit agencies: Implementing winning KPIs. Hoboken, N. J: Wiley.

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